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cs.LG2026
PoSafeNet: Safe Learning with Poset-Structured Neural Nets
Kiwan Wong, Wei Xiao, Daniela Rus
Safe learning is essential for deploying learningbased controllers in safety-critical robotic systems, yet existing approaches often enforce multiple safety constraints uniformly o…
cs.LG2025
DataS^3: Dataset Subset Selection for Specialization
Neha Hulkund, Alaa Maalouf, Levi Cai +15
In many real-world machine learning (ML) applications (e.g. detecting broken bones in x-ray images, detecting species in camera traps), in practice models need to perform well on s…
cs.LG2024
ABNet: Attention BarrierNet for Safe and Scalable Robot Learning
Wei Xiao, Tsun-Hsuan Wang, Daniela Rus
Safe learning is central to AI-enabled robots where a single failure may lead to catastrophic results. Barrier-based method is one of the dominant approaches for safe robot learnin…